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Erschienen in:
2020 | OriginalPaper | Buchkapitel
3. Wearable Design and Computing
verfasst von : Bin Fang, Fuchun Sun, Huaping Liu, Chunfang Liu, Di Guo
Erschienen in: Wearable Technology for Robotic Manipulation and Learning
Verlag: Springer Singapore
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Abstract
Wearable design and computing are up to the performance of the wearable device. In this chapter, we introduce the wearable device that comprises eighteen low-cost inertial and magnetic measurement units (IMMUs). It makes up the drawbacks of traditional data glove which only captures incomplete gesture information. The IMMUs are designed compact and small enough to wear on the upper-arm, forearm, palm, and fingers. The orientation algorithms including Quaternion Extended Kalman Filter (QEKF) and two-step optimal filter are presented. We integrate the kinematic models of the arm, hand, and fingers into the whole system to capture the motion gesture. A position algorithm is also deduced to compute the positions of fingertips. Experimental results demonstrate that the proposed wearable device can accurately capture the gesture.